Is Trend Following Dead in 2026? “The trend is your friend until the bend at the end.” We’ve all heard it. But in the algorithmic warfare of 2026, relying on simple Moving Average (MA) crossovers or basic Golden Crosses is a recipe for disaster. The market has become noisier, and “whipsaws” (false signals in sideways … Read more
We’ve all seen the hype: “Build a trading bot in 5 minutes with AI!” But as recent developer confessions and research have revealed, the reality of Vibe Coding often feels less like a “Flow State” and more like “Debugging Hell.” For those of us adhering to the Google Antigravity protocol (a safety-first architecture), blind coding … Read more
👋 Welcome Back, Vibe Coders! In [Part 1], we built the “Hard Memory” folder structure to give our AI a brain. Now, we need to give it eyes and hands. Most beginners tell their AI: “Make me a dashboard.” And the AI responds with a React app that auto-refreshes every second. Result? Your IP gets … Read more
Let’s be honest: Most retail trading bots fail. Why? Because they are built on “surface-level” logic found in basic blog posts: “Buy when RSI is under 30” or “Buy when price hits the lower Bollinger Band.” In the world of High-Frequency Trading (HFT), that is just liquidity for the sharks. I wanted to change that. … Read more
Hello, everyone! 👋 In our previous posts, we discussed how to design powerful trading strategies like the “US Closing Price Betting System” using Google’s Gemini and NotebookLM. A common question I get is: “How do I feed the AI better data to make it smarter?” The answer is simple: Quality Input = Quality Output. To … Read more
Have you tried the new “Gems” feature in Google Gemini yet? If you are a developer or a trader, this is an absolute game-changer. For a long time, I’ve wanted to build a Python-based automated trading system based on Mark Minervini’s VCP (Volatility Contraction Pattern) strategy. But translating visual chart patterns into rigorous mathematical code … Read more